The Korean Association for the Study of English Language and Linguistics

Korean Journal of English Language and Linguistics - Vol. 24
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Korea Journal of English Language and Linguistics - Vol. 24, No. 0, pp. 441-459
Abbreviation: KASELL
ISSN: 1598-1398 (Print) 2586-7474 (Online)
Print publication date 31 Jan 2024
Received 29 Dec 2023 Revised 29 Apr 2024 Accepted 02 May 2024
DOI: https://doi.org/10.15738/kjell.24..202405.441

Developing AI Chatbots for Pragmatic Instruction of Korean Secondary L2 English Learners
Min-Chang Sung ; Sooyeon Kang
(First author) Associate Professor, Department of English Education, Gyeongin National University of Education Sammak-ro 155, Manan-gu, Anyang-si Gyeonggi-do, 13910, Republic of Korea, Tel: +82-31-470-6335 (mcsung@ginue.ac.kr)
(Corresponding author) English Teacher, Sinyeon Middle School Moraenae-ro 408, Seodaemun-gu, Seoul, 03717, Republic of Korea, Tel: +87-2-379-4317 (englishsk329@naver.com)


© 2024 KASELL All rights reserved
This is an open-access article distributed under the terms of the Creative Commons License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract

This study explores the design and application of AI chatbots tailored for L2 English pragmatic instruction. Addressing the importance of pragmatic competence alongside the challenges faced by L2 learners, we developed four chatbots through Dialogflow CX and integrated them onto web user interfaces to examine the effectiveness of the AI chatbots in L2 pragmatic learning. We invited a cohort of six middle school students to practice the conversations in pragmatically intensive (i.e., PDR-high) situations. Our findings reveal the need for a dual structure in chatbot design, a separation of technological operation from dialogic content, and a pair-wise page design for cohesive conversations. Additionally, user interfaces should offer contextual clues and linguistic supports to assist learners in understanding and navigating pragmatic exchanges. The participants’ positive perceptions highlight the chatbots’ effectiveness in improving pragmatic awareness and knowledge, akin to other dialogue-based computer-assisted language learning systems. However, the need for guiding feedback mechanisms and inclusive training data for chatbot development has also been noted. In conclusion, chatbots show promise for L2 pragmatic instruction especially when their design architectures and user interfaces carefully reflect dialogue contents, information technology, and supportive elements for effective learner interaction.

Keywords: L2 pragmatic instruction, PDR-high request, AI chatbot, Dialogflow CX, user interface
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